OxDX validating 'deep learning' technology that identifies diseases ‘while you wait’
The company is aiming to bring to market an ultra-fast analysis platform capable of rapidly scaling to many diseases via simple software updates; it wants to improve speed, cost, and accuracy of diagnostics worldwide.
OxDX uses novel universal labelling technology in combination with machine learning analysis in a neural network to rapidly identify the specific pathogens causing infection.
A University of Oxford spin out, OxDX claims the AI powered diagnostic tool can recognize and identify specific species and strains of viruses, bacteria, and other pathogens within a sample in seconds.
The team said they have already demonstrated the ability of the technology to identify respiratory viruses in clinical samples and, in the case of COVID-19 and influenza viruses, to directly identify the strain.
Investors
The pre-seed funding was co-led by IQ Capital and Ahren Innovation Capital with participation from Science Creates Ventures. the capital will be used to expand the team and further validate the technology with development partners, said OxDX.
Alex Batchelor, CEO, OxDX, said: “Our ability to take a sample from someone with an unknown infection and answer the open question ‘what do they have?’ within a minute is a gamechanger for infection diagnosis and treatment.
“We’ll start with respiratory viruses and expand from there. In parallel, we’ll be simplifying the workflow to move the test from the lab to point of care, which will represent a step change in the availability and cost of infectious disease diagnostics worldwide.”
When asked what the company’s anticipated timeline to commercialization is following technology validation, he told BioPharma-Reporter: “We anticipate getting our first diagnostic test product to market in late 2024.”
OxDX’s development partners include hospital labs and private clinics. To date, those testing organizations have been UK based. “But we are open to collaborating further afield,” added Batchelor.
